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*EASTBIO* Sound and Vision Technology, and AI for Improved Prawn Aquaculture

Project Description

BBSRC Thematic Group: Livestock & Aquaculture

Recirculating Aquaculture Systems (RAS) offer exciting potential for revolutionising protein production, and could underpin food security. Understanding the behaviour of cultured animals is key to optimising production, assisting with best husbandry practise and maximizing welfare. We will apply new video and acoustic technological approaches, and data analysis using AI methods and computer vision, to improve understanding of cultured White Leg Prawns.

We will use stereo videography to observe 3D swimming activity of prawns in tanks, and document aspects of group behaviour including nearest neighbour analysis, for example as has been done for Antarctic krill (Murphy et al. 2019). This will inform optimisation of aquaculture stocking densities. We will record the underwater soundscape in tanks and look for correlations with behaviour and time since feeding. There is a growing awareness of the importance of sound to crustaceans, that have not traditionally been thought of as ‘vocal’ animals (Coquereau et al. 2016): it may be possible to move towards on-demand feeding if there are auditory cues to hunger.

The video and acoustic sampling will deliver very large volumes of data. We will explore application of cutting-edge computer vision and AI techniques to extract patterns from data and maximise the inferences that can be made from the behavioural observations. Computer vision technologies have a great deal to offer aquaculture (Zion, 2012). All data together may lead to development of improved methods for RAS cultivation, that in turn will deliver higher yields from more efficient, high-welfare aquaculture for a greener bioeconomy. The project will provide training across of suite of biological disciplines, and leave the student well equipped for a career in research, aquaculture or big data.

Funding Notes

This project is eligible for the EASTBIO Doctoral Training Partnership: View Website

This opportunity is only open to UK nationals (or EU students who have been resident in the UK for 3+ years immediately prior to the programme start date) due to restrictions imposed by the funding body.

Apply by 5.00 pm on 13 April 2020 following the instructions on how to apply at: View Website


Coquereau, L. et al. (2016). Acoustic behaviours of large crustaceans in NE Atlantic coastal habitats. Aquatic Biology, 25: 151
Murphy, D. et al. (2019). Three dimensional spatial structure of Antarctic krill schools in the laboratory. Scientific Reports, 9: 381
Zion, B. (2012). The use of computer vision technologies in aquaculture – a review. Computers and Electronics in Agriculture, 88: 125.

How good is research at University of St Andrews in Biological Sciences?

FTE Category A staff submitted: 50.45

Research output data provided by the Research Excellence Framework (REF)

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